Intelligent evaluation method and system for urban public space quality based on multi-source data

Abstract

The application relates to a kind of urban public space quality intelligent evaluation method and system based on multi-source data, the method includes obtaining the urban public area to be evaluated set by space quality query subject on space evaluation interface and current evaluation precision level, and obtaining the traffic evaluation coefficient and social activity evaluation coefficient stored in advance according to the urban public area to be evaluated;Get the region building model corresponding to the urban public area to be evaluated and the corresponding basic model data, generate updated region building model and updated basic model data;Extract road traffic data, extract road use data and social activity data;Generate urban space quality evaluation score.The present application realizes the generation of urban space quality score on the basis of meeting the needs of the space quality query subject, meeting the concern dimension of the urban space user in the urban public area to be evaluated, realizing intelligent and comprehensive intelligent evaluation.

Description

TECHNICAL FIELD

[0001] The application relates to the technical field of urban planning, in particular to an intelligent evaluation method and system for urban public space quality based on multi-source data. BACKGROUND

[0002] Urban public space refers to an open space body existing between building entities in a city or urban agglomeration, which is an open place for urban residents to carry out public communication and hold various activities, and its purpose is to serve the general public.

[0003] At present, there are various evaluation methods for urban public space. For example, a visual urban street space quality evaluation grading method is disclosed in Chinese Patent No. CN115203803A on October 18, 2022, which comprises the following steps: Step 1, constructing an urban street design quality evaluation method based on user perception experience; Step 2, drawing a street design space quality grading map, establishing a street design quality database based on street space form data and street scene picture data, using a large amount of street scene picture data and machine learning score algorithm intelligent and digital technical means to establish a quantitative model between street design space quality evaluation indexes and influencing factors, and obtaining the quality scores of all streets by substituting all street scene pictures in the selected area into the above-mentioned urban street design quality evaluation model and drawing a scatter plot.

[0004] Although the technical solution in the above-mentioned patent document can realize in-depth analysis of the street space quality distribution and influencing factors of the research area and improve the accuracy of urban street quality problem diagnosis, it is similar to other analysis methods in the prior art and cannot meet the fine element control requirements, and there are still problems of inaccurate and incomplete analysis caused by analyzing a larger area. SUMMARY

[0005] Therefore, it is necessary to provide an intelligent evaluation method and system for urban public space quality based on multi-source data, which can perform fine, multi-dimensional, high-precision, comprehensive and integrated quality evaluation on the urban public space of a smaller area.

[0006] The technical solution of the application is as follows:

[0007] An intelligent evaluation method for urban public space quality based on multi-source data, the method comprising:

[0008] obtaining the urban public area to be evaluated set by the space quality query subject on the space evaluation interface and the current evaluation accuracy level, and obtaining the pre-stored traffic evaluation coefficient and social activity evaluation coefficient according to the urban public area to be evaluated;

[0009] obtain the to-be-evaluated regional building model corresponding to the to-be-evaluated urban public area and the corresponding basic model data, update the to-be-evaluated regional building model and the basic model data according to the current evaluation accuracy level, and generate an updated regional building model and updated basic model data;

[0010] extract road traffic data according to the updated regional building model, and extract road use data and social activity data according to the updated basic model data;

[0011] generate an urban space quality evaluation score according to the road traffic data, the road use data, and the social activity data based on the traffic evaluation coefficient and the social activity evaluation coefficient.

[0012] Optionally, the to-be-evaluated urban public area and the current evaluation accuracy level set by the space quality query subject on the space evaluation interface are obtained; the method comprises the following steps:

[0013] obtain the initial urban public area and the current evaluation accuracy level set by the space quality query subject on the space evaluation interface;

[0014] obtain the query subject identity information of the space quality query subject, compare the query subject identity information with a pre-stored public area query level library, and generate a sensitive public area corresponding to the space quality query subject;

[0015] remove the initial urban public area according to the pre-stored sensitive public area, and generate a preliminary screening urban public area;

[0016] generate an associated public area according to the preliminary screening public area, and aggregate the preliminary screening public area and the associated public area to generate a to-be-delineated public area;

[0017] obtain regional planning data of the to-be-delineated public area from a preset quality evaluation setting time to a current determination time, and extract an estimated change space area from the regional planning data;

[0018] extract an estimated change area of the estimated change space area, and generate a change area ratio according to a total area of the to-be-delineated public area and the estimated change area;

[0019] determine whether the change area ratio is greater than or equal to a preset standard area ratio;

[0020] If the judgment is yes, a region evaluation adjustment suggestion is generated, the region evaluation adjustment suggestion is sent to the space quality query subject, region adjustment data of the space quality query subject is acquired, the preliminary screening urban public region is adjusted according to the region adjustment data, and the to-be-evaluated urban public region is generated after the adjustment;

[0021] If the judgment is no, the to-be-evaluated urban public region is set according to the preliminary screening urban public region.

[0022] Optionally, the to-be-evaluated region building model corresponding to the to-be-evaluated urban public region and corresponding basic model data are acquired, the to-be-evaluated region building model and the basic model data are updated according to the current evaluation precision level, and updated region building model and updated basic model data are generated; comprising:

[0023] The to-be-evaluated region building model corresponding to the to-be-evaluated urban public region and corresponding basic model data are acquired, and model update record data of the to-be-evaluated region building model are acquired;

[0024] In response to acquiring the model update record data, an update determination time period and a model update qualified number of times are acquired according to the current evaluation precision level;

[0025] The model data actual update number of times in the update determination time period is extracted from the model update record data;

[0026] It is judged whether the model data actual update number of times is greater than or equal to the model update qualified number of times;

[0027] If the judgment is yes, the to-be-evaluated region building model and the basic model data are set as updated region building model and updated basic model data;

[0028] If the judgment is no, a model update instruction is generated, the to-be-evaluated region building model and the basic model data are updated according to the model update instruction, and updated region building model and updated basic model data are generated.

[0029] Optionally, based on the traffic evaluation coefficient and the social activity evaluation coefficient, a city space quality evaluation score is generated according to the road traffic data, the road use data and the social activity data; comprising:

[0030] Based on the traffic evaluation coefficient, a road traffic evaluation score is generated according to the road traffic data and the road use data;

[0031] Based on the social activity evaluation coefficient, a social activity evaluation score is generated according to the social activity data;

[0032] Add the road traffic evaluation score and the social activity evaluation score to generate a city space quality evaluation score.

[0033] Optionally, based on the traffic evaluation coefficient, a road traffic evaluation score is generated according to the road traffic data and the road use data; the method comprises the following steps:

[0034] Extract street used road and corresponding road area information, road occupation information, road bending information and road flatness information of each street used road from the road traffic data, wherein the number of the street used roads is n, and the street used road is a street that has been put into use in the public area of the city to be evaluated;

[0035] Calculate the total area of each single road of the street used road;

[0036] Extract the road occupation area in each street used road and the total legal occupation area in each street used road from the road occupation information, wherein one street used road corresponds to one road occupation area, the road occupation area is the area occupied by obstacles in the street used road, and the total legal occupation area is the sum of the area occupied by the area pre-marked by the road management department in each street used road;

[0037] According to the road bending information, extract the actual road bending of each street used road, and count the actual bending times of the actual road bending;

[0038] Screen out the actual road bending corresponding to the actual bending times greater than the preset standard bending times, and record it as an overload bending, and obtain the difference value between the actual bending times corresponding to the overload bending and the standard bending times, and record it as an overload bending number, wherein the number of the overload bending is m, and one overload bending corresponds to one overload bending number;

[0039] Extract the road flatness of each street used road from the road flatness information;

[0040] Based on the traffic evaluation coefficient, according to each single road total area, road occupation area, total legal occupation area, overload bending number, standard bending times and road flatness, a road traffic evaluation score is generated by using the following formula:

[0041]

[0042] Wherein, TF is a road traffic evaluation score, δ is a traffic evaluation coefficient, n is the number of used roads in the street, Wsdi is the total area of the single road of the i-th used road in the street, Woci is the road occupation area of the i-th used road in the street, Wta is the total area of legal occupation, m is the number of overloaded bends, Ctj is the number of overloaded bends of the j-th overloaded bend, Cs is the standard number of bends, and Tir is the road flatness.

[0043] Optionally, a city public space quality intelligent evaluation system based on multi-source data, the system comprises:

[0044] An evaluation space determination module is configured to acquire a to-be-evaluated city public area and a current evaluation precision level set by a space quality query subject on a space evaluation interface, and acquire a pre-stored traffic evaluation coefficient and a social activity evaluation coefficient according to the to-be-evaluated city public area;

[0045] A city model updating module is configured to acquire a to-be-evaluated regional building model corresponding to the to-be-evaluated city public area and corresponding basic model data, update the to-be-evaluated regional building model and the basic model data according to the current evaluation precision level, and generate updated regional building model and updated basic model data;

[0046] A space data extraction module is configured to extract road traffic data according to the updated regional building model, and extract road use data and social activity data according to the updated basic model data;

[0047] A quality evaluation generation module is configured to generate a city space quality evaluation score based on the traffic evaluation coefficient and the social activity evaluation coefficient, according to the road traffic data, the road use data and the social activity data.

[0048] Optionally, a computer device is also provided, comprising a memory and a processor, the memory stores a computer program, and the processor implements the steps of the above-mentioned city public space quality intelligent evaluation method based on multi-source data when executing the computer program.

[0049] Optionally, a computer readable storage medium is also provided, which stores a computer program, and the computer program implements the steps of the above-mentioned city public space quality intelligent evaluation method based on multi-source data when executed by a processor.

[0050] The present application realizes the following technical effects:

[0051] The above-mentioned urban public space quality intelligent evaluation method and system based on multi-source data successively obtains a to-be-evaluated urban public region set by a space quality query subject on a space evaluation interface and a current evaluation accuracy level, and obtains a pre-stored traffic evaluation coefficient and a social activity evaluation coefficient according to the to-be-evaluated urban public region; obtains a to-be-evaluated regional building model corresponding to the to-be-evaluated urban public region and corresponding basic model data, updates the to-be-evaluated regional building model and the basic model data according to the current evaluation accuracy level, and generates updated regional building model and updated basic model data; extracts road traffic data according to the updated regional building model, and extracts road use data and social activity data according to the updated basic model data; and generates an urban space quality evaluation score based on the traffic evaluation coefficient and the social activity evaluation coefficient, according to the road traffic data, the road use data and the social activity data. In order to solve the problem that the statistics of urban public space in the prior art is too general, the region of the space quality query subject is used to finely select the urban public space to be evaluated, the space evaluation interface is used to display all selectable urban public spaces, the to-be-evaluated urban public region is the region selected by the space quality query subject to be scored for urban space quality, and the current evaluation accuracy level is set by the space quality query subject to represent the accuracy of the evaluation of the selected region. The traffic evaluation coefficient is used to represent the degree of attention of the urban space user in the to-be-evaluated urban public region to traffic, and the social activity evaluation coefficient is used to represent the degree of attention of the urban space user in the to-be-evaluated urban public region to social activities. Then, in order to ensure that the current model is accurate and avoid the problem that the urban model is not updated in time or the data obtained by the crawler type data acquisition method is not accurate in the prior art, the to-be-evaluated regional building model corresponding to the to-be-evaluated urban public region and the corresponding basic model data are obtained, then the to-be-evaluated regional building model and the basic model data are updated according to the current evaluation accuracy level, and the updated regional building model and the updated basic model data are generated, the current evaluation accuracy level is set to update the model to different degrees, and the accuracy is improved while meeting the self-defined needs of the space quality query subject. Then, the road traffic data is extracted according to the updated regional building model, and the road use data and the social activity data are extracted according to the updated basic model data to realize more fine space evaluation data acquisition.Finally, based on the traffic evaluation coefficient and the social activity evaluation coefficient, the urban space quality evaluation score is generated according to the road traffic data, the road use data and the social activity data, so as to realize the generation of the urban space quality evaluation score on the basis of meeting the needs of the space quality query subject and meeting the concerned dimensions of the urban space use subject in the public urban area to be evaluated, and realize intelligent and comprehensive intelligent evaluation. BRIEF DESCRIPTION OF DRAWINGS

[0052] Figure 1 FIG. 1 is a flowchart of a method for intelligent evaluation of urban public space quality based on multi-source data according to an embodiment.

[0053] Figure 2 FIG. 2 is a structural block diagram of an intelligent evaluation system for urban public space quality based on multi-source data according to an embodiment. DETAILED DESCRIPTION

[0054] In order to make the purposes, technical solutions and advantages of the present application clearer, the present application will be further described in detail below with reference to the drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and do not limit the present application.

[0055] In one embodiment, a terminal is provided, which is configured to: acquire a public urban area to be evaluated and a current evaluation precision level set by a space quality query subject on a space evaluation interface, and acquire a pre-stored traffic evaluation coefficient and a social activity evaluation coefficient according to the public urban area to be evaluated; acquire a to-be-evaluated regional building model corresponding to the public urban area to be evaluated and corresponding basic model data, update the to-be-evaluated regional building model and the basic model data according to the current evaluation precision level, and generate updated regional building model and updated basic model data; extract road traffic data according to the updated regional building model, and extract road use data and social activity data according to the updated basic model data; and generate an urban space quality evaluation score according to the road traffic data, the road use data and the social activity data based on the traffic evaluation coefficient and the social activity evaluation coefficient.

[0056] The terminal can be, but is not limited to, various personal computers, notebook computers, smart phones, tablet computers and portable wearable devices.

[0057] In one embodiment, as shown in FIG. 1, a method for intelligent evaluation of urban public space quality based on multi-source data is provided, which comprises the following steps. Figure 1

[0058] ​Step S100: obtaining the urban public area to be evaluated and the current evaluation accuracy level set by the spatial quality query subject on the spatial evaluation interface, and obtaining the pre-stored traffic evaluation coefficient and social activity evaluation coefficient based on the urban public area to be evaluated;

[0059] Step S200: obtaining a building model of the area to be evaluated and corresponding basic model data corresponding to the urban public area to be evaluated, updating the building model of the area to be evaluated and the basic model data according to the current evaluation accuracy level, and generating an updated building model of the area to be evaluated and updated basic model data;

[0060] Step S300: extracting road traffic data based on the updated regional building model, and extracting road use data and social activity data based on the updated basic model data;

[0061] Step S400: Based on the traffic evaluation coefficient and the social activity evaluation coefficient, an urban space quality evaluation score is generated according to the road traffic data, the road usage data and the social activity data.

[0062] In this embodiment, in order to solve the problem that the statistics of urban public space in the prior art is too general, the region demarcation for the space quality query subject is adopted to finely select the urban public space to be evaluated, specifically, the urban public region to be evaluated set by the space quality query subject on the space evaluation interface and the current evaluation accuracy level are obtained, and the pre-stored traffic evaluation coefficient and social activity evaluation coefficient are obtained according to the urban public region to be evaluated. The space evaluation interface is used to display all the selectable urban public spaces, the urban public region to be evaluated is the region selected by the space quality query subject to be scored for the urban space quality, and the current evaluation accuracy level is set by the space quality query subject, which is used to represent the accuracy of the evaluation of the selected region. The traffic evaluation coefficient is used to represent the degree of attention of the urban space user in the urban public region to be evaluated to traffic, and the social activity evaluation coefficient is used to represent the degree of attention of the urban space user in the urban public region to be evaluated to social activities. Then, in order to ensure that the current model is accurate and avoid the problem that the urban model is not updated in time in the prior art or the problem that the data obtained by the crawler type data acquisition method is not accurate, the region building model to be evaluated corresponding to the urban public region to be evaluated and the corresponding basic model data are obtained, then the region building model to be evaluated and the basic model data are updated according to the current evaluation accuracy level to generate updated region building model and updated basic model data, and the current evaluation accuracy level is set to update the model to different degrees, which improves the accuracy and meets the customized needs of the space quality query subject. Then, the road traffic data is extracted according to the updated region building model, and the road use data and social activity data are extracted according to the updated basic model data to realize more refined space evaluation data acquisition. Finally, based on the traffic evaluation coefficient and the social activity evaluation coefficient, the urban space quality evaluation score is generated according to the road traffic data, the road use data and the social activity data, which realizes the generation of the urban space quality score based on meeting the needs of the space quality query subject and meeting the attention dimensions of the urban space users in the urban public region to be evaluated, and realizes intelligent and comprehensive intelligent evaluation.

[0063] Specifically, the in-degree of traffic and social activities of multiple urban space users is investigated, and in-degree feedback data of traffic and social activities of multiple urban space users is obtained, and traffic feedback scores and social activity feedback scores are generated according to the traffic in-degree feedback data; the average values of each traffic feedback score and the social activity feedback score are calculated respectively, different average values set different coefficients, the higher the average value, the higher the coefficient, that is, the higher the traffic evaluation coefficient and the social activity evaluation coefficient, so that by generating the traffic evaluation coefficient and the social activity evaluation coefficient, the quality evaluation of urban public space based on the urban space user can be realized, more specifically, and more in line with the use of urban space.

[0064] In one embodiment, step S100: obtaining the urban public area to be evaluated and the current evaluation precision level set by the space quality query subject on the space evaluation interface; comprising:

[0065] Step S110: obtaining the initial urban public area and the current evaluation precision level set by the space quality query subject on the space evaluation interface;

[0066] Step S120: obtaining the query subject identity information of the space quality query subject, comparing the query subject identity information with the pre-stored public area query level library, and generating a sensitive public area corresponding to the space quality query subject;

[0067] Step S130: removing the initial urban public area according to the pre-stored sensitive public area, and generating a preliminary screening urban public area;

[0068] Step S140: generating an associated public area according to the preliminary screening public area, and summarizing the preliminary screening public area and the associated public area to generate a to-be-delineated public area;

[0069] Step S150: obtaining the regional planning data of the to-be-delineated public area from the current determination time to the preset quality evaluation setting time, and extracting a predicted change space area from the regional planning data;

[0070] Step S160: extracting the predicted change area of the predicted change space area, and generating a change area ratio according to the total area of the to-be-delineated area of the to-be-delineated public area and the predicted change area;

[0071] Step S170: determining whether the change area ratio is greater than or equal to a preset standard area ratio;

[0072] Step S180: If the judgment is yes, a region evaluation adjustment suggestion is generated, the region evaluation adjustment suggestion is sent to the space quality query subject, region adjustment data of the space quality query subject is obtained, the preliminary screening urban public region is adjusted according to the region adjustment data, and an urban public region to be evaluated is generated after adjustment;

[0073] Step S190: If the judgment is no, an urban public region to be evaluated is set according to the preliminary screening urban public region.

[0074] In the embodiment, the quality evaluation setting time is set in advance, and is generally set to a time between 3-6 months in order to prevent the problem that the area to be evaluated needs to be adjusted in a short time, resulting in the current evaluation being meaningless. In order to ensure that the area to be evaluated is evaluable and subsequent evaluation is accurate, the initial urban public area and the current evaluation accuracy level set by the space quality query subject on the space evaluation interface are first obtained, and then the query subject identity information of the space quality query subject is obtained, the query subject identity information is compared with the pre-stored public area query level library, and the sensitive public area corresponding to the space quality query subject is generated. The public area query registration library pre-stores a plurality of standard identity levels and a standard non-public area corresponding to the standard identity level. That is, a standard identity level subject corresponds to a standard non-public area. The standard non-public area is a pre-set area that is not disclosed to the subject corresponding to the standard identity level. This setting allows only subjects of a specific level to query specific areas, thereby achieving the leakage of space area quality evaluation information. After obtaining the query subject identity information of the space quality query subject, the query subject identity information can be analyzed, specifically by analyzing according to a pre-set identity analysis dimension, the identity analysis dimension including name, affiliated unit, position, visit purpose, etc., each identity analysis dimension corresponding to a score, and the total score being obtained after the scores are added. The correspondence between the identity level and the score is pre-set, so after the total score is obtained, the actual identity level of the space quality query subject can be generated according to the identity analysis dimension. Then, the actual identity level is compared with the standard identity level in the public area query level library, and the standard identity level identical to the actual identity level is screened out, and the standard non-public area corresponding to the screened standard identity level is set as the sensitive public area corresponding to the space quality query subject. The sensitive public area includes but is not limited to the public security bureau and the police station. The sensitive public area can also include schools, secret-related research institutions, and the like. That is, if the space quality query subject is a general visitor, the quality score of an area similar to a police station or a public security bureau cannot be queried. Then, the initial urban public area is excluded according to the pre-stored sensitive public area, and an initial screening urban public area is generated; and an associated public area is generated according to the initial screening public area, and the initial screening public area and the associated public area are summarized to generate a to-be-delineated public area. The associated public area is a region that is connected to the initial screening public area and has a traffic intercommunication relationship and a social interaction relationship. The traffic intercommunication relationship means that the connection between two regions can be realized relatively conveniently through public transportation, and the commuting time is within 20 minutes. The social interaction relationship means that the social interaction between two regions can be realized relatively conveniently through public transportation.The area related to the area to be evaluated is taken into account by generating the to-be-delineated public area by aggregating the preliminary screening public area and the associated public area, thereby improving the accuracy and comprehensiveness of the evaluation area. The area planning data of the to-be-delineated public area is obtained from the current determination time to the preset quality evaluation setting time, and the estimated change space area is extracted from the area planning data. Then, the estimated change area of the estimated change space area is extracted, and the change area ratio is generated according to the ratio of the total area of the to-be-delineated area of the to-be-delineated public area to the estimated change area. Then, it is judged whether the change area ratio is greater than or equal to the preset standard area ratio. If the judgment is yes, the area evaluation adjustment suggestion is generated, and the area evaluation adjustment suggestion is sent to the space quality query subject, and the area adjustment data of the space quality query subject is obtained. The preliminary screening urban public area is adjusted according to the area adjustment data, and the to-be-evaluated urban public area is generated after adjustment. If the judgment is yes, that is, the change area ratio is greater than or equal to the preset standard area ratio, which means that the change area is large at this time, which leads to the fact that the subject using the area to be evaluated generates data with too large variability when using the area, so that the collected data cannot accurately perform high-precision quality evaluation, or even if the quality evaluation is performed, it only has reference value for a short time and loses reference value after the quality evaluation setting time, which leads to useless quality evaluation work. Therefore, the suggestion is generated, suggesting that the space quality query subject reselects the area, changes the selected area or stops the evaluation of the area, that is, the area evaluation adjustment suggestion is sent to the space quality query subject, and the area adjustment data of the space quality query subject is obtained. The preliminary screening urban public area is adjusted according to the area adjustment data, and the to-be-evaluated urban public area is generated after adjustment. If the judgment is no, the to-be-evaluated urban public area is set according to the preliminary screening urban public area. In this step, if the judgment is no, it means that the planning change area does not reach the degree of affecting the overall area evaluation at this time, so the area evaluation can be normally performed, and the accuracy of the quality evaluation will not be affected by subsequent planning. The standard area ratio is set in advance and can be set to 10%, generally less than 10%. Thus, the to-be-evaluated urban public area can be directly set according to the preliminary screening urban public area.

[0075] In one embodiment, step S200: obtaining the to-be-evaluated area building model and the corresponding basic model data corresponding to the to-be-evaluated urban public area, updating the to-be-evaluated area building model and the basic model data according to the current evaluation accuracy level, and generating updated area building model and updated basic model data; comprising:

[0076] Step S210: Obtain the to-be-evaluated regional building model corresponding to the to-be-evaluated urban public area and the corresponding basic model data, and obtain the model update record data of the to-be-evaluated regional building model;

[0077] Step S220: In response to obtaining the model update record data, obtain the update determination time period and the model update qualified number according to the current evaluation accuracy level;

[0078] Step S230: Extract the actual model data update number in the update determination time period from the model update record data;

[0079] Step S240: Determine whether the actual model data update number is greater than or equal to the model update qualified number;

[0080] Step S250: If the determination is yes, set the to-be-evaluated regional building model and the basic model data as the updated regional building model and the updated basic model data;

[0081] Step S260: If the determination is no, generate a model update instruction, update the to-be-evaluated regional building model and the basic model data according to the model update instruction, and generate the updated regional building model and the updated basic model data.

[0082] In this embodiment, the city public space model database is pre-collected and stored, so that after the city public area to be evaluated is obtained, it can be compared with the city public space model database, and the corresponding evaluation area building model and the corresponding basic model data of the city public area to be evaluated are obtained. The evaluation area building model is updated in real time according to the setting of the actual manager. In order to meet the needs of quality evaluation at present, it is necessary to judge whether the requirement of update frequency is met according to different needs. Specifically, the model update record data of the evaluation area building model is obtained, and then the update determination time period and the model update qualified number are obtained according to the current evaluation accuracy level. The current evaluation accuracy level corresponds to the update determination time period and the model update qualified number. The higher the current evaluation accuracy level, the higher the accuracy requirement, so the time span of the update determination time period is longer, and the value of the model update qualified number is larger, that is, the higher the accuracy requirement, the longer the time of investigation, and the more frequent the update, so as to ensure that the model data used at present is relatively accurate. In this application, the standard evaluation level and the corresponding standard determination time period, and the standard update qualified number corresponding to the standard determination time period are set in advance. When the current evaluation accuracy level is obtained, the standard determination time period and the standard update qualified number corresponding to the standard evaluation level same as the current evaluation accuracy level are set as the update determination time period and the model update qualified number by comparing with each standard evaluation level. Then, the actual model data update number in the update determination time period is extracted from the model update record data, and then it is judged whether the actual model data update number is greater than or equal to the model update qualified number. If the judgment is yes, it means that the number of model updates is large at this time, and the fine degree of model update meets the standard, so the subsequent city space quality evaluation can be carried out, so the evaluation area building model and the basic model data are set as the updated area building model and the updated basic model data. If the judgment is no, it means that the number of model updates is small in a certain time period, and the fine degree is not high, which affects the subsequent space quality evaluation, so the model needs to be updated in time, so the model update instruction is generated, and the evaluation area building model and the basic model data are updated according to the model update instruction, and the updated area building model and the updated basic model data are generated.

[0083] In one embodiment, in step S260, the evaluation area building model and the basic model data are updated according to the model update instruction, and the updated area building model and the updated basic model data are generated, including:

[0084] Step S261: According to the model update instruction, the update time closest to the current determination time in the actual update times of the model data is obtained, and the time of this update is set as the latest model update time, wherein the building model corresponding to the latest model update time is the building model to be updated, and the building model to be updated corresponds to the basic data to be updated;

[0085] Step S262: Obtain the building environment monitoring data uploaded by the urban space environment management subject in the time period from the latest model update time to the current determination time.

[0086] Step S263: Generate a building environment update node according to the building environment monitoring data, and update the building model to be updated and the basic data to be updated according to the building environment update node to generate an updated regional building model and updated basic model data.

[0087] In this embodiment, the urban space environment management subject is a management personnel who monitors the urban public space through environmental monitoring sensors and manual monitoring methods. Therefore, on the basis of the existing basic model, in order to avoid the problems of low data processing efficiency, long processing time, and repeated data collection caused by large-scale re-determination of urban space data, the latest update time is obtained, and the model and data corresponding to the latest update time are updated. Specifically, according to the model update instruction, the update time closest to the current determination time in the actual update times of the model data is obtained, and the time of this update is set as the latest model update time, wherein the building model corresponding to the latest model update time is the building model to be updated, and the building model to be updated corresponds to the basic data to be updated. Among them, the update time closest to the current determination time is the latest time, for example, if the current determination time is the real-time time, the update times are 3, the first one is 3 months ago, the second one is 2 months ago, and the third one is 15 days ago, then the latest update time is 15 days ago. Then, in order to save resources, the building environment monitoring data uploaded by the urban space environment management subject in the time period from the latest model update time to the current determination time is obtained. Then, according to the building environment monitoring data, a building environment update node is generated, which is a point where the space environment changes, such as a changed road node, an added bus station, and a widened auxiliary road. Then, the building model to be updated and the basic data to be updated are updated according to the building environment update node to generate an updated regional building model and updated basic model data.

[0088] In one embodiment, after generating the updated regional building model and the updated basic model data in step S263, the following steps are further included:

[0089] First, a random environment comparison quantity is generated according to the total area of the region to be demarcated, then a matching number of random comparison model regions are screened out from the updated regional building model according to the random environment comparison quantity, and the urban space environment management subject is instructed to conduct field monitoring and obtain a field comparison building region according to the random comparison model region; then, the field comparison building region is compared with the random comparison model region, and a model comparison similarity is generated. It is judged whether the model comparison similarity reaches 98%. If the answer is yes, a current model qualified indication is generated. If the answer is no, a similarity difference between the model comparison similarity and 98% is obtained, and when the similarity difference is greater than a preset similarity threshold, a model review indication is generated, and the urban space environment management subject is guided to conduct model review and data update according to the model review indication. After the review and data update are completed, the latest updated regional building model and updated basic model data are generated. In this way, through the re-determination mode, the model data obtained is further accurately ensured to match the actual building, the workload of model detection and data collection is saved, the accuracy is ensured, and the accuracy of subsequent urban space quality evaluation points is improved.

[0090] In one embodiment, step S400: based on the traffic evaluation coefficient and the social activity evaluation coefficient, generating a city space quality evaluation point according to the road traffic data, the road use data and the social activity data; includes:

[0091] Step S410: based on the traffic evaluation coefficient, generating a road traffic evaluation point according to the road traffic data and the road use data;

[0092] Step S420: based on the social activity evaluation coefficient, generating a social activity evaluation point according to the social activity data;

[0093] Step S430: adding the road traffic evaluation point and the social activity evaluation point to generate a city space quality evaluation point.

[0094] In this embodiment, the quality evaluation is performed from the road traffic and social life dimensions respectively, realizing comprehensive evaluation of the city space, specifically: based on the traffic evaluation coefficient, generating a road traffic evaluation point according to the road traffic data and the road use data; then based on the social activity evaluation coefficient and the social activity data, generating a social activity evaluation point; finally adding the road traffic evaluation point and the social activity evaluation point to generate a city space quality evaluation point.

[0095] In one embodiment, step S410: based on the traffic evaluation coefficient, generating a road traffic evaluation point according to the road traffic data and the road use data; includes:

[0096] Step S411: Extracting street used roads and corresponding road area information, road occupation information, road bending information and road flatness information of each street used road from the road traffic data, wherein the number of the street used roads is n, and the street used roads are streets that have been put into use in the public area of the city to be evaluated;

[0097] Step S412: Calculating the total area of each single road of the street used roads;

[0098] Step S413: Extracting road occupation area in each street used road and total legal occupation area in each street used road from the road occupation information, wherein one street used road corresponds to one road occupation area, the road occupation area is the area occupied by obstacles in the street used road, and the total legal occupation area is the sum of the area occupied by the area predefined by the road management department in each street used road;

[0099] For example, the area occupied by bus stations in each street used road;

[0100] Step S414: Extracting the actual road bending of each street used road according to the road bending information, and counting the actual bending times of the actual road bending;

[0101] Step S415: Screening out the actual road bending corresponding to the actual bending times greater than the preset standard bending times, denoted as overload bending, and obtaining the difference value between the actual bending times corresponding to the overload bending and the standard bending times, denoted as overload bending number, wherein the number of the overload bending is m, and one overload bending corresponds to one overload bending number;

[0102] Step S416: Extracting the road flatness of each street used road from the road flatness information;

[0103] In this step, the road flatness is obtained by the city space environment management subject using the fixed-length ruler method, the cross-section drawing method or the smooth accumulation method.

[0104] Step S417: Based on the traffic evaluation coefficient, generating the road traffic evaluation score according to the total area of each single road, road occupation area, total legal occupation area, overload bending number, standard bending times and road flatness using the following formula:

[0105]

[0106] Wherein, TF is the road traffic evaluation score, δ is the traffic evaluation coefficient, n is the number of street used roads, Wsdi is the total area of the single road of the i-th street used road, Woci is the road occupied area of the i-th street used road, Wta is the total legal occupied area, m is the number of overloaded bends, Ctj is the number of overloaded bends of the j-th overloaded bend, Cs is the standard bend frequency, and Tir is the road flatness.

[0107] In this embodiment, in order to calculate the score for measuring road traffic, first, the street used roads and the road area information, road occupation information, road bend information and road flatness information corresponding to each street used road are extracted from the road traffic data, and then the total area of the single road of each street used road is calculated. The calculation can be digitalized according to the obtained model, thereby improving the data processing efficiency. Then the total area of the single road of each street used road is calculated, and the road occupation area in each street used road and the total legal occupation area in each street used road are extracted from the road occupation information. One street used road corresponds to one road occupation area. Finally, the actual road bends of each street used road are extracted according to the road bend information, and the actual bend frequency of the actual road bends is counted. The actual road bends corresponding to the actual bend frequency greater than the preset standard bend frequency are screened out and recorded as overloaded bends. The difference between the actual bend frequency corresponding to the overloaded bends and the standard bend frequency is obtained and recorded as the number of overloaded bends. Then the road flatness of each street used road is extracted from the road flatness information. Finally, based on the traffic evaluation coefficient, the road traffic evaluation score is generated according to the total area of the single road, the road occupation area, the total legal occupation area, the number of overloaded bends, the standard bend frequency and the road flatness by using the following formula.

[0108] In one embodiment, step S420: generating a social activity evaluation score based on the social activity evaluation coefficient according to the social activity data, comprises:

[0109] Step S421: extracting a social activity block from the social activity data, and obtaining activity holding information, participant number information, block basic information and store data information of each social activity block;

[0110] Step S422: extracting the average holding frequency of the social activity block within a data collection period according to the activity holding information, and obtaining an activity frequency score according to the average holding frequency, wherein the data collection period is pre-set;

[0111] Step S423: extracting the average participant number of the social activity block within a data collection period according to the participant number information;

[0112] Step S424: extracting the block actual area and the block green area according to the block basic information, and generating the number of opened stores of the social active block within a preset range according to the store data information;

[0113] Step S425: generating the social activity evaluation score according to the average number of holding, the average number of participants, the block actual area, the block green area and the number of opened stores based on the social activity evaluation coefficient by using the following formula:

[0114]

[0115] wherein, SA is the social activity evaluation score, ε is the social activity evaluation coefficient, N is the number of social active blocks, Agk is the activity number score of the kth social active block, Apk is the average number of participants of the kth social active block within the data collection period, Bak is the block actual area of the kth social active block, and Gak is the block green area of the kth social active block.

[0116] In the embodiment, the social active block is an area for the subject of urban space to rest and carry out entertainment, and the social active block is extracted according to the social active data, and then the activity holding information, the participant number information, the block basic information and the store data information of each social active block are obtained. The activity holding information is information when a social activity such as a party or an exhibition is held in the social active block, and the participant information is information related to participants obtained by registering information, collecting by a camera and data processing when the activity is held. The block basic information includes information such as the area of the region, the green area, the activity region, the health region and the parking region. The store data information is information related to the opened store. Then, the average number of holding within the data collection period is extracted according to the activity holding information, and the activity number score is obtained according to the average number of holding, wherein the data collection period is set in advance, such as one month, and data statistics is performed in units of one month, the number of holding in each month is counted, the average value is calculated, and finally the average number of holding is obtained. The average number of holding is obtained, and then the residents are investigated according to the average number of holding, and the satisfaction score of the residents is obtained, the average value is calculated according to each satisfaction score, and finally the activity number score is generated. The average number of participants within the data collection period is extracted according to the participant number information. The block actual area and the block green area are extracted according to the block basic information, and the number of opened stores of the social active block within a preset range is generated according to the store data information, and finally the social activity evaluation score is generated.

[0117] In one embodiment, after generating the urban space quality evaluation score, the method further comprises the following steps:

[0118] First, a classic deep neural network (DNN) model in artificial intelligence algorithm is selected, and the collected and used street quality measurement data such as road traffic data, road use data and the social activity data, and the corresponding quality score results, i.e. urban space quality evaluation score, are modeled and trained to generate a street space quality intelligent evaluation model.

[0119] The construction method of the street space quality intelligent evaluation model is as follows:

[0120] First, the overall model is constructed without considering the street type, and then three sub-models are constructed considering the differences of landscape, life and commercial street types.

[0121] Specifically, after specific debugging, the structure parameters of the neural network model can be set as follows: the all-type street quality prediction model has three hidden layers, respectively containing 384, 64 and 32 neurons, and each hidden layer is provided with a ReLU activation function and a dropout operation of 0.05, and the last layer contains a full connection layer with 32 inputs and 1 output.

[0122] The landscape, life and commercial street quality prediction models have three hidden layers, respectively containing 168, 64 and 32 neurons, and each hidden layer is provided with a ReLU activation function and a dropout operation of 0.01, and the last layer contains a full connection layer with 32 inputs and 1 output.

[0123] In addition, the goodness of fit can be set as follows: all-type street space quality evaluation model = 0.58; landscape street space quality evaluation model = 0.52; commercial street space quality evaluation model = 0.52; and life street space quality evaluation model = 0.50. Thus, the complex nonlinear relationship between the main and guest factors and the quality score can be learned through the model, and the quality score of other unused street space can be scored according to the scene setting. Therefore, efficient use of street urban space quality related data is achieved.

[0124] After generating the urban space quality evaluation score, a city space quality analysis report can also be generated according to the data. For example, the city space quality analysis report is as follows:

[0125] Appropriate human flow can increase the street vitality quality, but when the human flow is overloaded, the street quality will decrease. For a 200-meter-long commercial street, the quality score is the highest when the instantaneous human flow is less than 30. If there are 3-4 groups of communicating people and the rest of the groups of loitering people in the front space of the building, the combination is the best. For example, due to being located in the intersection area, Xudong Street often attracts a large number of human flow, and the complex interlaced traffic flow line seriously reduces the quality of Xudong Street.

[0126] In one embodiment, as shown in Figure 2 a city public space quality intelligent evaluation system based on multi-source data is also provided, and the system comprises:

[0127] An evaluation space determination module is configured to acquire a to-be-evaluated city public area and a current evaluation precision level set by a space quality query subject on a space evaluation interface, and acquire a pre-stored traffic evaluation coefficient and a social activity evaluation coefficient according to the to-be-evaluated city public area;

[0128] A city model updating module is configured to acquire a to-be-evaluated area building model corresponding to the to-be-evaluated city public area and corresponding basic model data, update the to-be-evaluated area building model and the basic model data according to the current evaluation precision level, and generate updated area building model and updated basic model data;

[0129] A space data extraction module is configured to extract road traffic data according to the updated area building model, and extract road use data and social activity data according to the updated basic model data;

[0130] A quality evaluation generation module is configured to generate a city space quality evaluation score based on the traffic evaluation coefficient and the social activity evaluation coefficient, according to the road traffic data, the road use data, and the social activity data.

[0131] In one embodiment, the evaluation space determination module is further configured to:

[0132] Obtain the initial urban public area set by the spatial quality query subject on the spatial evaluation interface and the current evaluation precision level; obtain the query subject identity information of the spatial quality query subject, compare the query subject identity information with the pre-stored public area query level library, and generate a sensitive public area corresponding to the spatial quality query subject; exclude the initial urban public area according to the pre-stored sensitive public area, and generate a preliminary screening urban public area; generate an associated public area according to the preliminary screening public area, and aggregate the preliminary screening public area and the associated public area to generate a to-be-delineated public area; obtain the regional planning data of the to-be-delineated public area from the current measurement time to the preset quality evaluation setting time, and extract the estimated variable space area from the regional planning data; extract the estimated variable area of the estimated variable space area, and generate a variable area ratio according to the total area of the to-be-delineated area of the to-be-delineated public area and the estimated variable area; determine whether the variable area ratio is greater than or equal to a preset standard area ratio; if the determination is yes, generate a regional evaluation adjustment suggestion, send the regional evaluation adjustment suggestion to the spatial quality query subject, obtain the regional adjustment data of the spatial quality query subject, adjust the preliminary screening urban public area according to the regional adjustment data, and generate a to-be-evaluated urban public area after adjustment; if the determination is no, set a to-be-evaluated urban public area according to the preliminary screening urban public area.

[0133] In one embodiment, the urban model updating module is further configured to:

[0134] Obtain the to-be-evaluated regional building model corresponding to the to-be-evaluated urban public area and the corresponding basic model data, and obtain the model updating record data of the to-be-evaluated regional building model; in response to obtaining the model updating record data, obtain an update measurement time period and a model updating qualified number of times according to the current evaluation precision level; extract the actual number of model data updates in the update measurement time period from the model updating record data; determine whether the actual number of model data updates is greater than or equal to the model updating qualified number of times; if the determination is yes, set the to-be-evaluated regional building model and the basic model data as an updated regional building model and updated basic model data; if the determination is no, generate a model updating instruction, update the to-be-evaluated regional building model and the basic model data according to the model updating instruction, and generate an updated regional building model and updated basic model data.

[0135] In an embodiment, the urban model updating module is further configured to: obtain, according to the model updating instruction, an update time closest to a current determination time from the actual number of model data updates, and set the update time as a latest model update time, wherein the building model corresponding to the latest model update time is a building model to be updated, and the building model to be updated corresponds to building data to be updated; obtain building environment monitoring data uploaded by the urban space environment management subject in a time period from the latest model update time to the current determination time; generate a building environment update node according to the building environment monitoring data, and update the building model to be updated and the building data to be updated according to the building environment update node to generate an updated regional building model and updated building model data.

[0136] In an embodiment, the urban model updating module is further configured to: generate a random environment comparison number according to the total area of the region to be delineated, then select a matching number of random comparison model regions from the updated regional building model according to the random environment comparison number, and instruct the urban space environment management subject to perform on-site monitoring and obtain an on-site comparison building region according to the random comparison model region; then, compare the on-site comparison building region with the random comparison model region, and generate a model comparison similarity. Determine whether the model comparison similarity reaches 98%, if the determination is yes, generate a current model qualified indication. If the determination is no, obtain a similarity difference between the model comparison similarity and 98%, and when the similarity difference is greater than a preset similarity threshold, generate a model review indication, and guide the urban space environment management subject to perform model review and data update according to the model review indication, and generate the latest updated regional building model and updated building model data after the review and data update are completed.

[0137] In an embodiment, the quality evaluation generation module is further configured to: generate a road traffic evaluation score according to the road traffic data and the road use data based on the traffic evaluation coefficient; generate a social activity evaluation score according to the social activity data based on the social activity evaluation coefficient; and add the road traffic evaluation score and the social activity evaluation score to generate a city space quality evaluation score.

[0138] In one embodiment, the quality evaluation generation module is further configured to: extract street used road and road area information, road occupation information, road bending information and road flatness information corresponding to each of the street used road from the road traffic data, wherein the number of the street used road is n, and the street used road is a street that has been put into use in the city public area to be evaluated; calculate a single road total area of each of the street used road; extract a road occupation area in each of the street used road and a total legal occupation area in each of the street used road from the road occupation information, wherein one of the street used road corresponds to one road occupation area, the road occupation area is an area occupied by an obstacle in the street used road, and the total legal occupation area is a sum of areas occupied by a region pre-defined by a road management department in each of the street used road; extract an actual road bending of each of the street used road according to the road bending information, and count an actual bending number of the actual road bending; screen out an actual road bending corresponding to an actual bending number greater than a preset standard bending number, denoted as an overload bending, and obtain a number difference between the actual bending number corresponding to the overload bending and the standard bending number, denoted as an overload bending number, wherein the number of the overload bending is m, and one of the overload bending corresponds to one of the overload bending number; extract a road flatness of each of the street used road from the road flatness information; and generate a road traffic evaluation score based on the traffic evaluation coefficient according to each of the single road total area, the road occupation area, the total legal occupation area, the overload bending number, the standard bending number and the road flatness, using the following formula:

[0139]

[0140] wherein TF is the road traffic evaluation score, δ is the traffic evaluation coefficient, n is the number of the street used road, Wsd i is the single road total area of the i th street used road, Woc i is the road occupation area of the i th street used road, Wta is the total legal occupation area, m is the number of the overload bending, Ct j is the overload bending number of the j th overload bending, Cs is the standard bending number, and Tir is the road flatness.

[0141] In one embodiment, the quality evaluation generation module is further configured to: extract a social activity block according to the social activity data, and obtain activity holding information, participant number information, block basic information, and shop data information of each social activity block; extract an average holding number of the social activity block in a data collection period according to the activity holding information, and obtain an activity number score according to the average holding number, wherein the data collection period is pre-set; extract an average participant number of the social activity block in the data collection period according to the participant number information; extract a block actual area and a block green area according to the block basic information, and generate a number of opened shops in a preset range of the social activity block according to the shop data information; and generate a social activity evaluation score according to the average holding number, the average participant number, the block actual area, the block green area, and the number of opened shops in the preset range based on the social activity evaluation coefficient by using the following formula:

[0142]

[0143] wherein SA is the social activity evaluation score, ε is the social activity evaluation coefficient, N is the number of social activity blocks, Agk is the activity number score of the kth social activity block, Apk is the average participant number of the kth social activity block in the data collection period, Bak is the block actual area of the kth social activity block, and Gak is the block green area of the kth social activity block.

[0144] The quality evaluation generation module is further configured to perform the following steps:

[0145] The overall model is constructed without considering the street type, and then three sub-models are constructed considering the differences among landscape, life, and commercial street types.

[0146] Specifically, after specific debugging, the structure parameters of the neural network model can be set as follows: the overall street quality prediction model has three hidden layers, respectively containing 384, 64, and 32 neurons, a ReLU activation function and a dropout operation of 0.05 are set after each hidden layer, and the last layer contains a full connection layer with 32 inputs and 1 output.

[0147] The landscape, life, and commercial street quality prediction models have three hidden layers, respectively containing 168, 64, and 32 neurons, a ReLU activation function and a dropout operation of 0.01 are set after each hidden layer, and the last layer contains a full connection layer with 32 inputs and 1 output.

[0148] In addition, the goodness of fit can be set as: the full type street space quality evaluation model = 0.58; the landscape street space quality evaluation model = 0.52; the commercial street space quality evaluation model = 0.52; and the living street space quality evaluation model = 0.50. Thus, the complex nonlinear relationship between the main and guest factors and the quality score can be learned through the model, and the quality of other unused street spaces can be scored according to the scene setting. Therefore, the efficient use of the street urban space quality related data is realized.

[0149] The quality evaluation generation module is further configured to perform the following steps: the urban space quality analysis report can also be generated according to the data. For example, the urban space quality analysis report is as follows:

[0150] The appropriate flow of people can increase the street vitality quality, but when the flow of people is overloaded, the street quality will decrease. For a 200-meter-long commercial street, the quality score is the highest when the instantaneous flow is less than 30. If there are 3-4 groups of communicating people and the rest of the groups of loitering people in the front space of the building, the combination is the best. For example, due to being in the intersection, Xudong Street often attracts a large flow of people, and the complex interlaced traffic flow seriously reduces the quality of Xudong Street.

[0151] In one embodiment, a computer device is provided, which includes a memory and a processor, the memory stores a computer program, and the processor implements the steps of the above-mentioned urban public space quality intelligent evaluation method based on multi-source data when executing the computer program.

[0152] In one embodiment, a computer readable storage medium is also provided, which stores a computer program, and the computer program implements the steps of the above-mentioned urban public space quality intelligent evaluation method based on multi-source data when executed by a processor.

[0153] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer readable storage medium, and when the computer program is executed, the processes of the above-mentioned embodiments of the methods can be included. Any reference to memory, storage, databases, or other media in the embodiments provided by the present application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration but not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0154] Any combination of the technical features of the above embodiments can be made. In order to make the description simple, all possible combinations of the technical features in the above embodiments are not described, however, as long as the combination of the technical features does not exist, it should be considered as the scope of the present application.

[0155] The above embodiments only express several embodiments of the present application, and the description is more specific and detailed, but it should not be understood as a limitation on the scope of the patent. It should be noted that for ordinary skilled in the art, without departing from the concept of the present application, a number of modifications and improvements can be made, which are within the scope of the present application. Therefore, the scope of the patent of the present application should be subject to the appended claims.

Claims

1. An intelligent evaluation method for urban public space quality based on multi-source data, characterized by: The method comprises: Obtaining the urban public area to be evaluated and the current evaluation accuracy level set by the spatial quality query subject on the spatial evaluation interface, and obtaining the pre-stored traffic evaluation coefficient and social activity evaluation coefficient based on the urban public area to be evaluated; Acquire a building model of the area to be evaluated and corresponding basic model data corresponding to the urban public area to be evaluated, update the building model of the area to be evaluated and the basic model data according to the current evaluation accuracy level, and generate an updated building model of the area to be evaluated and updated basic model data; Extracting road traffic data based on the updated regional building model, and extracting road use data and social activity data based on the updated basic model data; Based on the traffic evaluation coefficient and the social activity evaluation coefficient, generating an urban space quality evaluation score according to the road traffic data, the road use data and the social activity data; Obtain the urban public areas to be evaluated and the current evaluation accuracy level set by the spatial quality query subject on the spatial evaluation interface; including: Obtain the initial urban public area and current evaluation accuracy level set by the spatial quality query subject on the spatial evaluation interface; Obtaining the query subject identity information of the space quality query subject, comparing the query subject identity information with a pre-stored public area query grade library, and generating a sensitive public area corresponding to the space quality query subject; Eliminating the initial urban public areas according to pre-stored sensitive public areas, and generating preliminary screening urban public areas; Generate associated public areas based on the pre-screened urban public areas, and aggregate the pre-screened urban public areas and the associated public areas to generate a public area to be demarcated; Acquiring regional planning data of the public area to be demarcated between the current measurement time and a preset quality evaluation setting time, and extracting an estimated change spatial area from the regional planning data; Extracting an estimated change region area of ​​the estimated change spatial region, and generating a change region area ratio according to the total area of ​​the to-be-demarcated area of ​​the to-be-demarcated common area and the estimated change region area; Determining whether the area ratio of the variable region is greater than or equal to a preset standard region area ratio; If the judgment is yes, then generate a regional evaluation adjustment suggestion, send the regional evaluation adjustment suggestion to the spatial quality query subject, obtain regional adjustment data of the spatial quality query subject, adjust the initially screened urban public areas according to the regional adjustment data, and generate the urban public areas to be evaluated after the adjustment; If the judgment is no, then the urban public areas to be evaluated are set based on the initially screened urban public areas.

2. The intelligent evaluation method for urban public space quality based on multi-source data according to claim 1 is characterized in that: Obtaining a building model of the area to be evaluated and corresponding basic model data corresponding to the urban public area to be evaluated, updating the building model of the area to be evaluated and the basic model data according to the current evaluation accuracy level and generating an updated building model of the area and updated basic model data; including: Acquire the building model of the area to be evaluated and the corresponding basic model data corresponding to the urban public area to be evaluated, and acquire the model update record data of the building model of the area to be evaluated; In response to acquiring the model update record data, acquiring an update measurement time period and a number of qualified model update times according to the current evaluation accuracy level; extracting the actual number of model data updates within the update measurement time period from the model update record data; Determining whether the actual number of model data updates is greater than or equal to the qualified number of model updates; If the judgment is yes, setting the building model of the area to be evaluated and the basic model data as the updated building model of the area and the updated basic model data; If the judgment is no, a model update instruction is generated, and the building model of the area to be evaluated and the basic model data are updated according to the model update instruction, and an updated regional building model and updated basic model data are generated.

3. The intelligent evaluation method for urban public space quality based on multi-source data according to claim 1 is characterized in that: Based on the traffic evaluation coefficient and the social activity evaluation coefficient, an urban space quality evaluation score is generated according to the road traffic data, the road use data and the social activity data; including: generating a road traffic evaluation score based on the road traffic data and the road usage data based on the traffic evaluation coefficient; generating a social activity evaluation score based on the social activity data based on the social activity evaluation coefficient; The road traffic evaluation score and the social activity evaluation score are added together to generate an urban space quality evaluation score.

4. The intelligent evaluation method for urban public space quality based on multi-source data according to claim 3 is characterized in that: Generating a road traffic evaluation score based on the road traffic data and the road usage data based on the traffic evaluation coefficient; comprising: Extracting from the road traffic data the road area information, road occupancy information, road bend information, and road smoothing information corresponding to each of the used streets, wherein the number of the used streets is n, and the used streets are streets that have been put into use in the public area of ​​the city to be evaluated; Calculate the total individual road area of ​​used roads for each of the streets; Extracting the road occupation area of ​​each of the used roads on the street and the legally occupied total area of ​​each of the used roads on the street from the road occupation information, wherein one used road on the street corresponds to one road occupation area, the road occupation area is the area occupied by obstacles on the used road on the street, and the legally occupied total area is the sum of the areas occupied by areas pre-demarcated by the road management department on the used roads on the street; Extracting actual road bends of used roads of each of the streets according to the road bend information, and counting the actual number of bends of the actual road bends; Screening out actual road bends corresponding to actual bend counts greater than a preset standard bend count, recording them as overload bends, and obtaining a difference between the actual bend counts corresponding to the overload bends and the standard bend counts, recording the difference as the overload bend count, wherein the number of overload bends is m, and one overload bend corresponds to one overload bend count; Extracting the road smoothness of each of the used roads in the street from the road smoothness information; Based on the traffic evaluation coefficient, the road traffic evaluation score is generated using the following formula according to the total area of ​​each individual road, the road occupied area, the legal occupied area, the number of overload bends, the number of standard bends, and the road smoothness: ； Among them, TF is the road traffic evaluation score, is the traffic evaluation coefficient, n is the number of used roads in the street, Wsdi is the total area of ​​individual roads in the used roads of the i-th street, Woci is the road occupied area of ​​the used roads of the i-th street, Wta is the total legal occupied area, m is the number of overload bends, Ctj is the number of overload bends of the j-th overload bend, Cs is the number of standard bends, and Tir is the road smoothness.

5. The intelligent evaluation method for urban public space quality based on multi-source data according to claim 4 is characterized in that: Generating a social activity evaluation score based on the social activity data based on the social activity evaluation coefficient includes: Extracting socially active blocks based on the socially active data, and obtaining event information, participant number information, block basic information, and store data information for each socially active block; Extracting the average number of times the socially active block is held within a data collection period based on the event information, and obtaining an event frequency score based on the average number of times held, wherein the data collection period is preset; Extracting the average number of participants in the socially active block during the data collection period based on the participant number information; Extracting the actual area and green area of ​​the block according to the basic information of the block, and generating the number of opened stores within a preset range of the socially active block according to the store data information; Based on the social activity evaluation coefficient, the social activity evaluation score is generated using the following formula according to the average number of events, the average number of participants, the actual area of ​​the block, the green area of ​​the block, and the number of opened stores: ； Among them, SA is the social activity evaluation score, is the social activity evaluation coefficient, N is the number of socially active blocks, Agk is the activity score of the number of activities held in the kth socially active block, Apk is the average number of participants in the kth socially active block during the data collection period, Bak is the actual block area of ​​the kth socially active block, and Gak is the block green area of ​​the kth socially active block.

6. An intelligent urban public space quality evaluation system based on multi-source data, characterized by: The system comprises: The evaluation space determination module is used to obtain the urban public area to be evaluated and the current evaluation accuracy level set by the spatial quality query subject on the spatial evaluation interface, and obtain the pre-stored traffic evaluation coefficient and social activity evaluation coefficient based on the urban public area to be evaluated; a city model updating module, configured to obtain a building model of the area to be evaluated and corresponding basic model data corresponding to the public area of ​​the city to be evaluated, update the building model of the area to be evaluated and the basic model data according to the current evaluation accuracy level, and generate an updated building model of the area to be evaluated and updated basic model data; a spatial data extraction module, configured to extract road traffic data based on the updated regional building model, and to extract road use data and social activity data based on the updated basic model data; A quality evaluation generation module, configured to generate an urban space quality evaluation score based on the traffic evaluation coefficient and the social activity evaluation coefficient and according to the road traffic data, the road usage data, and the social activity data; The evaluation space determination module is further configured to: Obtain the initial urban public area and the current evaluation accuracy level set by the spatial quality query subject on the spatial evaluation interface; obtain the query subject identity information of the spatial quality query subject, compare the query subject identity information with the pre-stored public area query level library, and generate the sensitive public area corresponding to the spatial quality query subject; eliminate the initial urban public area according to the pre-stored sensitive public area, and generate a preliminary screening urban public area; generate associated public areas based on the preliminary screening urban public area, and aggregate the preliminary screening urban public area and the associated public areas to generate a public area to be demarcated; obtain the regional planning data of the public area to be demarcated between the current measurement time and the preset quality evaluation setting time, and Extract the estimated change spatial area from the regional planning data; extract the estimated change regional area of ​​the estimated change spatial area, and generate a change regional area ratio based on the total area of ​​the to-be-demarcated area of ​​the public area to be demarcated and the estimated change regional area; judge whether the change regional area ratio is greater than or equal to a preset standard area ratio; if it is judged to be yes, generate a regional evaluation adjustment suggestion, send the regional evaluation adjustment suggestion to the spatial quality query subject, obtain the regional adjustment data of the spatial quality query subject, adjust the pre-screened urban public area according to the regional adjustment data, and generate the urban public area to be evaluated after the adjustment; if it is judged to be no, set the urban public area to be evaluated based on the pre-screened urban public area.

7. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 5 are implemented.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 5 are implemented.

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